Environmental Management (2020) 66:549–563https://doi.org/10.1007/s00267-020-01328-y

The Knowledge and Value Basis of Private Forest Management inSweden: Actual Knowledge, Confidence, and Value Priorities

Louise Eriksson 1● Clas Fries2

Received: 10 March 2020 / Accepted: 29 June 2020 / Published online: 21 July 2020© The Author(s) 2020

AbstractWith growing demands on forests, there is a need to understand the drivers of managing the forest for diverse objectives,such as production, recreation, and climate adaptation. The aim of this study was to examine the knowledge and value basisof forest management behaviors, including different management strategies and management inactivity, among private forestowners in Sweden. Different dimensions of knowledge (declarative and procedural knowledge, assessed in terms ofobjective and subjective knowledge measures) and value priorities (basic values and forest values), as well as the roleof forest owner identity, were examined. The study was conducted by means of a postal questionnaire to a random sample ofprivate forest owners in Sweden (n= 3000, response rate 43%). The distinctions between actual knowledge (objectiveknowledge), confidence (subjective knowledge), and value priorities, in addition to the hierarchical structure of how thesefactors are linked to management behaviors, proved to be valuable. Results revealed that different knowledge dimensionsand value priorities were jointly important for forest management behaviors. In addition, the role of forest owner identity formanagement behaviors was confirmed. Insights from the study may be used to develop policy and outreach to private forestowners and thereby facilitate different forest functions in private forestry.

Keywords Forest management behavior ● Production ● Biodiversity ● Recreation ● Climate adaptation ● Climate mitigation

Introduction

In 2015, the United Nations agreed on 17 SustainableDevelopment Goals to be achieved by 2030 and how forestsare managed have implications for the attainment of severalof these goals, for example clean water and sanitation(goal 6), affordable and clean energy (goal 7), climateaction (goal 13), and life on land, including sustainableforest management (goal 15) (United Nations 2015). In thiscontext, there are growing societal demands to use andmanage the forest for production (e.g., timber), biodiversity

conservation, carbon sequestration (through carbon storageor carbon substitution), and people’s health and wellbeing(Bellassen and Luyssaert 2014; Jactel et al. 2017; Lagergrenand Jönsson 2017; Trivino et al. 2017). In addition, there isa need to reduce forests’ vulnerability to disturbancesthrough, for example, climate change adaptation (Lindneret al. 2014). To facilitate diverse forest functions or multi-objective forestry, policy-makers, and practitioners need anunderstanding of the underlying basis for managementdecisions. In countries with a significant share of privatelyowned forests (e.g., the US, Germany, Sweden, and Fin-land), decisions concerning how to manage the forest are inthe hands of family forest owners, also called individualprivate forest owners.

Previous research on forest owners has examined deter-minants of management activities, such as harvesting, themanagement of insects and invasive species, climate changeadaptation, wildlife practices, and participation in differentprograms (e.g., concerning conservation). Results haverevealed that structural characteristics relating to the ownerand the forest (e.g., gender, age, forest type, size of forest,and distance from roads) are associated with managementactivities (e.g., Joshi and Arano 2009; Lidestav and Berg

* Louise Erikssonlouise.eriksson@umu.se

1 Department of Geography, Umeå University, SE-901 87Umeå, Sweden

2 Forest Unit, Swedish Forest Agency, Box 284, SE-901 06Umeå, Sweden

Supplementary information The online version of this article (https://doi.org/10.1007/s00267-020-01328-y) contains supplementarymaterial, which is available to authorized users.

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Lejon 2013; Silver et al. 2015; Coté et al. 2016; Aguilaret al. 2017; Thompson et al. 2017; Floress et al. 2019). Inaddition, social and psychological factors, such as socialnetworks, personal experience, forest values and manage-ment objectives, subjective knowledge or awareness, andbeliefs and attitudes have been found to be important forengagement in particular activities (Karppinen 2005; Joshiand Arano 2009; Blennow et al. 2012; Hendee and Flint2013; Thompson and Hansen 2013; Põllumäe et al. 2014;Sagor and Becker 2014; Drescher et al. 2017; Kelly et al.2017; Eriksson 2017, 2018b; Vulturius et al. 2018; Fischer2019; Thorn et al. 2019). Even though knowledge has beenfound to play a role in forest management activities (e.g.,Floress et al. 2019), and lack of knowledge is considered asignificant barrier to achieving, in particular, new manage-ment aims such as climate change adaptation (Bissonnetteet al. 2017; Sousa-Silva et al. 2018), the complexitiesassociated with conceptualizing and measuring knowledgehave largely been ignored. In addition, scarce attention hasbeen given to the extent to which management decisions areformed based on knowledge as compared with other drivers.This study examined the knowledge and value basis offorest management in private forestry in Sweden. By usingtheoretically based concepts and carefully derived mea-sures, and by comparing the drivers of different manage-ment strategies and management inactivity, the studycontributes to an improved understanding of the underlyingbasis of forest management behaviors.

Theoretical Background

The institutional and social context, with roots in history,has obvious implications for how private forest manage-ment is conducted (Andersson and Keskitalo 2018; Nichi-forel et al. 2018). However, the heterogeneity among forestowners in the same setting suggests that the owners’ choiceof management strategy cannot be sufficiently explained bycontextual factors alone and a consideration of the psy-chological basis of management behaviors enables a morecomprehensive understanding (Ingemarson et al. 2006;Vulturius et al. 2018).

Knowledge and forest management

There are diverse forms of knowledge, including science-based, but also systems of indigenous or local knowledge(The Intergovernmental Science-Policy Platform on Biodi-versity and Ecosystem Services (IPBES) 2013; Hurlbertet al. 2019). In research on environmental behaviors, theindividuals’ knowledge is considered important for theformation of perceptions and behaviors (Kaiser and Fuhrer2003; Frick et al. 2004). However, there is a need to dis-tinguish between knowledge types and different measures

of knowledge (Vicente-Molina et al. 2013; Thorn andBogner 2018). Declarative or system knowledge—e.g., howenvironmental systems or certain aspects of a systemoperate—can be differentiated from procedural or action-related knowledge, referring to knowledge of the specificactions that can be implemented to achieve a certain goal(Kaiser and Fuhrer 2003; Frick et al. 2004; Díaz-Siefer et al.2015; Thorn and Bogner 2018). It is furthermore importantto distinguish between objective (or actual) and subjective(or self-rated) assessments of knowledge (Shi et al. 2016).Whereas measures of objective knowledge employ knowl-edge questions (true/false or multiple choice), subjectiveknowledge represents a self-assessment of, for example,familiarity, awareness, or level of knowledge (Steele et al.2006; Marzano et al. 2017), thus resembling the concept ofself-efficacy, i.e., the belief in one’s own ability to act(Bandura 1977) (Geiger et al. 2019a).

In relation to forest owners, mainly measures of sub-jective knowledge tapping different knowledge dimensionshave been employed, generally confirming an effect onmanagement activities (Eggers et al. 2014; Fischer andCharnley 2012; Steele et al. 2006; Germain et al. 2014). Forexample, Eggers et al. (2014) showed that higher subjectiveknowledge about management was related to using aproduction-focused management approach. In addition,research on environmental behaviors shows that whilesubjective knowledge has been found to be more closelyrelated to behavior, significant associations between objec-tive knowledge and behavior have also been confirmed(Vicente-Molina et al. 2013; Díaz-Siefer et al. 2015; but seeÜnal et al. 2017). Nevertheless, declarative objectiveknowledge have often been found to be indirectly related tobehavior via other types of knowledge (e.g., procedural andeffectiveness knowledge), attitudes, or intentions (Fricket al. 2004; Roczen et al. 2014; Kaiser and Fuhrer 2003;Nguyen et al. 2019).

Value priorities and forest management

Behaviors are also influenced by value priorities (Rohan2000). The cognitive hierarchy model stipulates that cog-nitions can be arranged in a hierarchy from more general tospecific cognitions (Fulton et al. 1996). On a general level,basic values transcend situations and act as general guidingprinciples for beliefs, attitudes, and behaviors. Schwartz’s(1992, 1994) value theory differentiates between twoindependent value dimensions; that is, values emphasizingself-interest (i.e., self-enhancement) versus others’ interests(i.e., self-transcendence, including altruistic and biosphericvalues) and values conveying an openness to new ideas(i.e., openness to change) versus maintaining the status quo(i.e., conservation). In addition, reasons why humans valueforests have been labeled forest values, general forest

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beliefs or value orientations, highlighting for example pro-duction, recreation, ecological, aesthetic, and cultural forestvalues (e.g., McFarlane and Boxall 2003; Eriksson et al.2013). In line with the cognitive hierarchy, associationsbetween basic values and forest values have been con-firmed, with self-transcendent values being positively cor-related with ecological and recreation forest values, butnegatively correlated with production values (Eriksson et al.2013).

Evidence supports the importance of value priorities formanagement decisions. For example, forest ownersemphasizing the interests of others and placing lessemphasis on more traditional values tend to be more likelyto participate in conservation programs (Drescher et al.2017), and stronger production forest values, but alsostronger ecological forest values, have been found to beassociated with climate change adaptation (Eriksson2018b). In addition, forest values have been incorporatedinto owner objectives, and the implementation of silvi-cultural measures, including thinning and harvesting, hasbeen found to be higher among owners emphasizing timberand forest income than among other owners (Põllumäe et al.2014; Joshi and Arano 2009). In contrast, an emphasis onamenity objectives has been found to be associated withlower levels of harvesting (Hendee and Flint 2013).

Forest owner identity and forest management

Self-identity refers to meanings attached to the self; andsince people are motivated to act in accordance with howthey view themselves, identity perceptions may influencebehaviors (Burke and Stets 2009; Walton and Emmet Jones2018). People generally have multiple identities that aremore or less central to the overall self and vary in relevanceacross contexts. Self-identities may, for example, be basedon group membership, such as forest ownership, with dif-ferent meanings associated with the identity. In addition,identity perceptions may contain a social dimensionreflecting the identification with a certain social group inconjunction with a differentiation from other groups. Sinceforest owners are heterogeneous, the meanings attached to aforest owner identity (FOI) may be diverse and cover sen-timents such as being a multi-objective owner, a recrea-tionist, economic centered, a farmer, an indifferent owner, aconservationist, multifunctional, or a self-employed owner,for example (Lawrence and Dandy 2014; Ní Dhubháin et al.2007; Ficko et al. 2017; Feliciano et al. 2017). Studiessuggest that perceptions of forest ownership may beincorporated as part of the owner’s identity (e.g., Bliss andMartin 1988; Lähdesmäki and Matilainen 2014; Kreye et al.2018; Bergstèn et al. 2018), although scarce attention hasbeen given to how different owner identities are associatedwith diverse management behaviors.

Conceptual framework

Based on the literature review, a conceptual frameworkdepicting psychological drivers of forest managementbehaviors was developed, including knowledge and valuepriorities (see Fig. 1). Whereas these drivers have evolvedconcurrently over time and are thus interlinked, the con-ceptual distinctions will facilitate theoretical developmentand be useful for practice. A multidimensional concept ofknowledge was employed (Shi et al. 2016), distinguishingbetween actual knowledge (objective knowledge) and con-fidence (subjective knowledge). The different concepts ofknowledge and value priorities were considered to behierarchically related to management behavior, with moregeneral factors (i.e., declarative knowledge and basicvalues) being more distal predictors than behavioral specificfactors (i.e., procedural knowledge and forest values) (Dietzet al. 1998; Gatersleben et al. 2017; Geiger et al. 2019b).Since forest owner identities reflect internalized perceptions(cf. Walton and Emmet Jones 2018), they should further-more be more closely associated with management thanknowledge and value priorities.

The Present Study

Although knowledge and value priorities are both con-firmed predictors of behaviors, their importance for forestmanagement behaviors has not been compared and dis-cussed. The aim of this study was to examine how actualknowledge, confidence and value priorities, as well as FOI,were associated with forest management behaviors amongprivate forest owners in Sweden. Whereas previous studiesof forest management activities have generally not

Actual knowledge

Objec�ve declara�ve knowledge

Objec�ve procedural knowledge

Confidence

Subjec�ve declara�ve knowledge

Subjec�ve procedural knowledge

Value priori�es

Basic values

Forest values

Forest owner iden�ty

Forest management behavior

Fig. 1 Conceptual framework of the hierarchically ordered knowledgeand value basis of forest management behaviors

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compared the determinants of different management stra-tegies (but see Joshi and Arano 2009), the present studyexplored predictors of different types of managementbehaviors, including management for production, biodi-versity, recreation, climate adaptation, and climate mitiga-tion. With thought to the changes in forest ownership inmany Western countries, e.g., more absentee owners andfewer owners relying on their forest for income (Hogl et al.2005; Ficko et al. 2017; Weiss et al. 2019), the determinantsof management inactivity were also explored. Overall, thestudy examined: (1) forest management behaviors (i.e.,frequency of engaging in different management strategies,including management inactivity, and relations betweenstrategies); (2) structural correlates of forest managementbehaviors, including gender, age, education, size of forestholding, residency, place, and region; and (3) the impor-tance of actual knowledge, confidence, value priorities, andFOI for forest management behaviors. Based on the con-ceptual framework, actual knowledge, confidence, andvalue priorities should all be associated with managementbehaviors. In addition, the psychological drivers wereexpected to be hierarchically ordered in relation to man-agement behaviors, with more general concepts being moredistant predictors than specific concepts. Whereas con-fidence is a key determinant of a broad range of behaviors(cf. Ajzen 2002), and both confidence and value prioritieshave been found to be relevant for forest management(Eggers et al. 2014; Eriksson 2018b), actual knowledge hasbeen given less attention. Thus, no hypotheses regarding therelative importance of the different knowledge dimensionsand value priorities for management behaviors weregenerated.

Materials and Methods

Study Area

Close to 70% of the land area in Sweden is covered byforests, and coniferous trees, primarily Norway Spruce andScots Pine, are the main tree species (Swedish University ofAgricultural Science [SLU] 2018). The majority of theforest in Sweden is privately owned, with ~50% owned byaround 330,000 individual private forest owners (SwedishForest Agency [SFA] 2014). The environmental and pro-duction objectives in the Swedish forest policy are con-sidered equally important, and forest is to be used for avariety of different purposes, including adapting it to cli-mate change and using it for climate mitigation (SwedishGov. Bill 2007/08:108). Nevertheless, the forest is a sig-nificant economic asset, with its large production ofroundwood and sawnwood (Eurostat 2017), and studieshave shown that the forestry culture in Sweden is dominated

by production objectives (e.g., Andersson and Keskitalo2018). Whereas management was regulated in detail before1993, with several mandatory silvicultural measures pre-venting management inactivity, only a few obligatorymeasures remain (e.g., regeneration after clear felling) andthe forest owners enjoy a great degree of freedom (Bush2010). In this context, information and advice are con-sidered important tools to achieve the goals of the forestpolicy (Johansson and Keskitalo 2014).

Respondents

A postal questionnaire to a randomly selected sample ofindividual private forest owners in Sweden, aged 20–80years and owning more than 5 ha of forest land, was con-ducted by a survey company (Attityd i Karlstad AB) in theautumn of 2018. After two reminders, the response rate was43% (n= 1251). The sample contained 19% women and themean age was 62 years (SD= 11). Almost a third of therespondents had a university degree (31%) and about half,52%, were resident owners. The mean area of productiveforest was 92 ha (SD= 260). Whereas differences betweenthe population and sample were minor, the sample didcontain fewer women, young owners, and owners withsmall forest properties. Hence, calibrated weights were usedin the analyses to control for these deviations.

Questionnaire

Information on gender, age, size of forest holding, andregion where the forest property was located were takenfrom the owner register. Background questions included,for example, education, whether the owner was resident ornonresident, and whether the owner lived in an urban or arural area. In addition, actual knowledge, confidence, valuepriorities, FOI, and forest management behaviors wereassessed in the questionnaire. Means, standard deviations,and internal reliability (alpha) for the psychological pre-dictors are displayed in the Appendix (Table A1).

Actual knowledge was examined using objectiveknowledge scales reflecting declarative knowledge aboutthe forest in Sweden more generally and proceduralknowledge in relation to each of the five management types.The construction of the knowledge scales was guided byresearch on how to measure knowledge (considering, e.g.,difficulty levels) (Frick et al. 2004; Díaz-Siefer et al. 2015)and forest facts, also involving a forest management expertat the SFA. The battery of questions at Skogskunskap.se (aweb portal with facts about forests) was used as inspirationfor some of the questions. The initial set of questions waspretested by a group of forest owners, answering thequestions and evaluating and commenting on their clarity,etc., as well as rating them on a three-point scale: easy,

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medium, or difficult. After revisions, six questions reflect-ing general knowledge (two for each of the three difficultylevels) and 20 questions reflecting the five types of proce-dural knowledge (including one easy, two medium, and onedifficult question on each of the scales) were included in thequestionnaire. A multi-response format was used, with threeto six correct response options for each question. Thequestions are available from the authors upon request.Answers were coded in three categories—0=wrong, 0.5=partly correct, and 1= correct—resulting in a scale from 0to 6 on general knowledge and a scale from 0 to 4 onprocedural knowledge.

Confidence was examined using subjective knowledgemeasures about the forest in general and about each of the fivemanagement types. Based on previous research on subjectiveknowledge (McFarlane and Watson 2008), the owners wereasked about how much knowledge they considered them-selves to have about the following: general knowledge aboutforests in Sweden (e.g., tree species, damage, and ownershipconditions); forest management aiming for good forestgrowth; forest management used to preserve biodiversity;forest management contributing to an attractive recreationforest; forest management aiming to use the forest for climatemitigation; and forest management adjusted to a warmer cli-mate. Answers were provided on a four-point scale (1= noknowledge at all, 2= a little knowledge, 3= certain knowl-edge, 4= extensive knowledge).

Value priorities in terms of basic values and three typesof forest values were assessed. Based on Schwartz’s(1992, 1994) value theory and the distinction betweenaltruistic, biospheric, and egoistic value orientations (deGroot and Steg 2008), the following basic values wereassessed: openness (five items), conservation (five items),self-enhancement (SE) (five items), and self-transcendence(ST) (including altruism (Alt) (four items) and biospheric(Bio) (four items)). The respondents were asked to indicatehow important each value was as a guiding principle in theirlife, with responses provided on a nine-point scale (−1=opposed to my values, 0= not important, 3= important,6= very important, and 7= extremely important). Beforecombining the values into higher-order value types, scaleuse differences were controlled for by mean centering thehigher-order value score as suggested by Schwartz. Aconfirmatory factor analyses with varimax rotation of thehigher-order value indexes (62% explained variance) con-firmed a two-factor model. Because of the relevance of theSE–ST scale for environmental behaviors (Stern 2000),only the factor scores based on this dimension were inclu-ded in the final analyses. To assess forest values, the ownerswere asked how important they believed production (e.g.,timber or biofuel), the possibilities for recreation forhumans, and biodiversity (diversity in plant and animal life)were in their own forest and in the Swedish forest in

general, respectively (cf. Eriksson 2018a). Answers wereprovided on a seven-point scale (1= not at all important,7= very important) and index variables were created bycalculating the means of the two items for each forestvalue scale.

Forest owner identity, in terms of the meanings attachedto the owners’ self- and social forest owner identities, aswell as centrality, was assessed. The owners were askedabout the extent to which they agreed with statementsreflecting how they use, manage, and perceive their forest(self-identity), and the extent to which they identified withdifferent types of other forest owners (social identity). Fourowner identities were measured, reflecting primary ways inwhich the forest may be perceived and used, relationshipswith other owners, and the forest itself; i.e., production andprivate asset (production/private), consumption of none-conomic values and public resource (consumption/public),connections with other owners (social), and detachmentfrom forest (distant). Answers were provided on a five-pointscale (1= totally disagree, 5= totally agree). Since theidentity scales had not been previously tested, alpha valuesguided their revisions. Removing any item from the SocialFOI or the Distant FOI did not increase the internal relia-bility. However, when one item was excluded from the tworemaining scales, the alpha values increased slightly. Ameasure of centrality of the forest to the owners wasdeveloped measuring positive emotions, the possession-selflink, and importance (six items) (cf. Ferraro et al. 2011).Answers were provided on a five-point response scale (1=totally disagree, 5= totally agree) and the mean of the itemswas used to create a centrality index. The distant and theconsumption/public FOI scales displayed a somewhat lowreliability (α= 0.65 and α= 0.62, respectively) and thisshould be considered when interpreting results. The FOIitems are provided in the Appendix (see Table A2).

Forest management behavior included the frequency ofimplementing different management strategies and man-agement inactivity. Production, biodiversity, recreation, andclimate adaptation management behaviors were examinedby means of four items each, and climate mitigation (interms of substitution) was assessed using three items. Theowners were asked about how often they had used differentstrategies in their forest and the answers were provided on afive-point scale (1= never, 2= seldom, 3= sometimes,4= often, 5= always) (see the Appendix (Table A3) for thelist of included management strategies). Subsequently, thesum of the included strategies was calculated, resulting in ascale from 1 to 20 for all management strategies exceptclimate mitigation (substitution), which had a scale from 1to 15. To assess management inactivity, the owners wereasked to indicate whether they had refrained from imple-menting any forest management measure during the last10 years.

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Analyses

For data analyses, SPSS Statistics 24 was utilized (IBMcorp. 2016). First, forest management behaviors weredescribed via means and standard deviations for the fivemanagement strategies and the percentage of owners dis-playing management inactivity. In addition, correlationsbetween management behaviors were analyzed usingPearson’s r for the management strategies and point-biserialcorrelation for management inactivity.

Second, linear regression analyses were used to examinerelations between structural characteristics and the differentmanagement strategies, and a binary logistic regressionanalysis was employed to analyze relations between struc-tural characteristics and management inactivity. Gender(dummy: 1= female), age, education (dummy: 1=Uni-versity degree), size of forest holding, residency (dummy:1= resident owner), place (dummy: 1= urban), and region(dummy: 1= South region corresponding to the organiza-tional setup of the SFA) were included as independentvariables. Dependent variables were management strategies(i.e., frequency of engaging in production, biodiversity,recreation, adaptation, and mitigation (substitution) man-agement) and management inactivity, respectively.

Third, the importance of knowledge, value priorities, andFOI for forest management behaviors was examined bymeans of hierarchical regression analyses in three steps.Linear regression analyses were used to examine predictorsof the different forest management strategies, and a binarylogistic regression analysis was employed to analyze pre-dictors of management inactivity. In the first step, generalvariables (i.e., declarative objective knowledge, declarativesubjective knowledge, and basic values) were included inthe analyses of both forest management strategies andmanagement inactivity. In the second step, the more specificknowledge and value variables (i.e., procedural objectiveknowledge, procedural subjective knowledge, and forest

values) were added. In the analyses of management strate-gies, one procedural knowledge measure and one forestvalue scale were examined in relation to each strategy (e.g.,procedural objective knowledge of production in relation toproduction management), except in relation to adaptationand mitigation (substitution) management. Since thesestrategies may be motivated by diverse forest values(Eriksson 2018a), both production and biodiversity forestvalues were included. In the analysis of management inac-tivity, all measures of actual knowledge, confidence, andforest values were used as predictors. Finally, in anexplorative manner, the Social FOI, the Distant FOI, andcentrality were included in relation to all managementstrategies. In addition, Production/private FOI was includedin relation to production management, consumption/publicFOI in relation to biodiversity and recreation management,and both these FOIs were examined in relation to adaptationand mitigation (substitution) management. The full set ofFOIs was included as predictors in the third step of theanalysis of management inactivity.

Results

Forest Management Behaviors

Descriptives and the associations between different mea-sures of forest management behaviors are displayed inTable 1. Whereas the owners did not frequently engage inmitigation (substitution) management, the means for theremaining strategies were close to the midpoint of the scale.About one fourth of the respondents had not engaged in anyforest management activities the last 10 years. The positivecorrelations between the strategies suggest that ownersimplementing one type of strategy were more likely toimplement the other strategies. A strong positive correlationwas found between climate adaptation management and

Table 1 Descriptives andbivariate correlations for forestmanagement behaviors

Productiona Biodiversitya Recreationa Adaptationa Mitigation(substitution)b

Managementinactivity

Production M= 10.27,SD= 3.44

Biodiversity 0.27*** M= 11.36,SD= 2.79

Recreation 0.26*** 0.48*** M= 10.74,SD= 3.65

Adaptation 0.43*** 0.53*** 0.54*** M= 10.98,SD= 3.74

Mitigation 0.41*** 0.21*** 0.31*** 0.39*** M= 4.79,SD= 1.85

Managementinactivity

−0.44*** −0.24*** −0.17*** −0.33*** −0.21*** 25.1%

***p < 0.001aScale 1–20, ranging from never to alwaysbScale 1–15, ranging from never to always

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both biodiversity and recreation management. In contrast,biodiversity management and climate mitigation (substitu-tion) management displayed the weakest correlation. Man-agement inactivity displayed the strongest negativecorrelation with production management, indicating thatinactive owners were the least likely to implementproduction-oriented activities.

Structural Characteristics and Forest ManagementBehaviors

Results from the regression analyses of how structuralcharacteristics are related to forest management behaviorsare displayed in Table 2. There was no evidence of colli-nearity, since no VIF value exceeded 1.303 in any of themodels. Results revealed that male owners, owners withlarger forest holdings, and owners in the south region hadimplemented all the management strategies to a greaterextent and were less likely to be inactive compared to theircounterparts. Older owners, compared with younger own-ers, had more frequently engaged in production, biodi-versity, and mitigation (substitution) management. Inaddition, owners with a university degree had more oftenimplemented biodiversity management, resident owners hadmore often implemented mitigation (substitution) manage-ment, and rural owners had more often employed recreationand adaptation management, compared to their counter-parts. The structural factors and forest characteristicsexplained between 5 and 8% of the variance in the differentmanagement strategies.

Psychological Drivers of Forest ManagementBehaviors

The hierarchical analyses of psychological drivers ofmanagement behaviors are displayed in Table 3 for theforest management strategies, and in Table 4 for man-agement inactivity. The models of forest managementstrategies displayed no evidence of collinearity (no VIFvalue exceeded 2.342). Among the general variables inthe first step, declarative subjective knowledge and basicvalues were significant predictors of all managementstrategies except recreation management, where onlydeclarative subjective knowledge was significant. In thesecond step the beta weights for the general variablesdecreased, although declarative subjective knowledge wasstill significant in relation to all management strategiesexcept production management, and basic values weresignificant in relation to production and mitigation (sub-stitution) management. Whereas procedural objectiveknowledge was a significant predictor in relation to pro-duction, biodiversity, and adaptation management, pro-cedural subjective knowledge, and forest values were

significant in relation to all management strategies. In thethird step, the beta weights of the more general variablesdecreased even further; however, procedural subjectiveknowledge was still significant in relation to all manage-ment strategies. In addition, basic values and productionvalues significantly determined production management,and production values were a significant predictor ofmitigation (substitution) management. Whereas the Pro-duction/private FOI predicted production and mitigation(substitution) management, the consumption/public FOIpredicted biodiversity, recreation, and adaptation man-agement. In addition, the social FOI was positively linkedto all management strategies and the Distant FOI wasnegatively associated with production, recreation, andadaptation management. Centrality of the identity waspositively correlated with recreation and adaptationmanagement. Two variables displayed reversed signs inthe final step of the analyses (declarative subjectiveknowledge in relation to production management anddeclarative objective knowledge in relation to adaptationmanagement), indicating that they act as suppressorvariables in these models. In each step of the analyses, theexplained variance increased significantly. Whereas thepredictors explained a relatively low level of variance inmitigation (substitution) management, they were moreimportant for production and adaptation management.

The analyses of forest management inactivity showedthat, in the first step, declarative objective and subjectiveknowledge were significant predictors but basic valueswere not. In subsequent steps, however, none of thesevariables remained significant. In the second step, pro-cedural objective knowledge of all forest managementstrategies except mitigation was significant, as was pro-cedural subjective knowledge of production and adap-tation. In addition, production forest values were asignificant predictor of management inactivity. Hence,whereas several different types of objective knowledgewere significant predictors of management inactivity,fewer measures of subjective knowledge, and forestvalues were. The same measures of procedural objectiveand subjective knowledge, in addition to productionforest values, remained significant in the third step. Inaddition, a weaker Production/private FOI and a weakerSocial FOI, but a stronger Distant FOI, were associatedwith management inactivity. Whereas less knowledgeand weaker production forest values were generallyassociated with a higher probability of not managing theforest, a higher level of procedural objective knowledgeof adaptation management was associated with man-agement inactivity. The full model was significantlybetter in explaining management inactivity compared tothe models with variables reflecting knowledge and valuepriorities.

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Discussion

This study confirms that different knowledge dimensionsand value priorities are jointly important for forest man-agement behaviors, adding to the ongoing discussion ofhow knowledge versus values influence behaviors (cf. Shiet al. 2016; Ünal et al. 2017; Bamberg and Möser 2007).These results are timely, and have implications for thefuture governance of private forestry, given the diversedemands on forest use and management (Lagergren andJönsson 2017). The study may further spur an interest for anovel knowledge approach in the context of adaptivemanagement where knowledge is considered a key asset(Fabricius and Cundill 2014).

The differential effects of knowledge on managementbehaviors shown in this study indicate that it is problematicto simply refer to knowledge as an important determinant(cf. Floress et al. 2019). Comparable to previous research inthe environmental domain (e.g., Frick et al. 2004), theresults generally supported the more remote role ofdeclarative compared to procedural knowledge in relation tomanagement behaviors, including management inactivity.Furthermore, procedural subjective knowledge was a sig-nificant predictor even in the final step of the analyses in allthe models, whereas results for procedural objectiveknowledge were less consistent. Hence, in line with pre-vious studies (Vicente-Molina et al. 2013; Eggerset al. 2014), the importance of subjective knowledge inrelation to diverse management strategies was supported.However, this study could not confirm that subjectiveknowledge was more important for management inactivity.Overall, the results verified a positive association betweenknowledge and forest management behaviors, irrespectiveof type of knowledge, with one exception: whereas beingmore knowledgeable about climate adaptation was asso-ciated with more frequently implementing adaptation mea-sures (e.g., increasing the share of mixed and broadleavedforest), it was also associated with management inactivity.A less proactive approach to the risk of future damages inforests has been found among less engaged owners (Ganet al. 2015). However, not implementing certain manage-ment measures may also reflect a willingness to rely on theforest’s own ability to adapt through evolutionary processes(i.e., passive adaptation) (Keskitalo et al. 2016; Hagermanand Pilai 2018).

By confirming the different value basis of production andmitigation (substitution) management versus biodiversitymanagement, and the dual value basis of climate adaptation,this study further expands on how the owners’ emphasis onSE versus ST values are relevant for forest managementbehaviors (e.g., Dreschel et al. 2017; Eriksson 2018a, b). Asexpected, the importance of basic values generallydecreased after the inclusion of more specific variables,Ta

ble2Structuralcharacteristicsas

predictors

offorestmanagem

entstrategies

andmanagem

entinactiv

ity

Production

Biodiversity

Recreation

Adaptation

Mitigatio

n(substitu

tion)

Managem

entinactiv

ity

B(SE)

βB(SE)

βB(SE)

βB(SE)

βB

(SE)

βB(SE)

Wald

Exp

(B)

Gender(1

=female)

−0.0814

(0.240)

−0.10***

−0.487(0.197)

−0.08*

−1.356(0.256)

−0.16***

−1.134(0.264)

−0.13***

−0.537(0.129)

−0.13***

0.410(0.171)

5.785*

1.507

Age

0.037(0.009)

0.12***

0.026(0.007)

0.11***

0.009(0.010)

0.03

0.018(0.010)

0.06

0.010(0.005)

0.06*

0.010(0.007)

2.293

1.010

Educatio

n(1

=University

)0.262(0.231)

0.04

0.925(0.190)

0.16***

0.456(0.246)

0.06

0.435(0.253)

0.06

0.144(0.124)

0.04

−0.147(0.173)

0.724

0.863

Sizeof

forestholding

0.004(0.001)

0.22***

0.001(0.000)

0.07*

0.001(0.001)

0.06*

0.002(0.001)

0.10***

0.001(0.000)

0.14***

−0.026(0.003)64.930***

0.974

Residency

(1=resident)

0.008(0.221)

0.00

0.175(0.182)

0.03

0.278(0.236)

0.04

0.377(0.242)

0.05

0.251(0.118)

0.07*

0.048(0.161)

0.089

1.049

Place

(1=urban)

−0.343(0.299)

−0.04

−0.423(0.246)

−0.06

−1.499(0.321)

−0.16***

−0.886(0.328)

−0.09**

−0.262(0.161)

−0.05

−0.384(0.225)

2.921

0.681

Region(1

=South)

0.558(0.208)

0.08**

0.818(0.171)

0.15***

0.822(0.222)

0.11***

1.141(0.228)

0.15***

0.686(0.112)

0.18***

−0.437(0.157)

7.709**

0.646

Constant

7.744(0.595)

9.243(0.489)

10.082

(0.635)

9.459(0.652)

3.843(0.319)

−0.731(0.451)

2.618

0.482

R2

0.08***

0.06***

0.08***

0.07***

0.09***

na

Adj

R2

0.07***

0.05***

0.07***

0.06***

0.08***

na

Nagelkerke

nana

nana

na0.201

−2Log

likelihood

nana

nana

na1100.71

nano

tapplicable

*p<0.05

;**p<0.01

;**

*p<0.00

1

556 Environmental Management (2020) 66:549–563

Table3Hierarchicallin

earregression

analyses

offorestmanagem

entstrategies

inthreesteps:(1)generalvariables(declarativ

ekn

owledg

eandbasicvalues),(2)specificvariables(procedu

ral

know

ledg

eandforestvalues),(3)forestow

neridentities

Produ

ction

Biodiversity

Recreation

Adaptation

Mitigatio

n(sub

stitu

tion)

B(SE)

βB(SE)

βB

(SE)

βB(SE)

βB(SE)

β

Step1

DEC-O

BJ

0.06

6(0.079

)0.02

0.12

3(0.065

)0.06

0.01

4(0.084

)0.01

0.09

6(0.082

)0.03

−0.02

0(0.044

)−0.01

DEC-SUBJ

1.44

5(0.141

)0.30

***

1.08

8(0.116

)0.28

***

1.44

4(0.151

)0.28

***

2.16

8(0.148

)0.41

***

0.53

5(0.079

)0.20

***

SE–ST

−0.46

0(0.096

)−0.14

***

0.30

2(0.079

)0.11

***

0.11

1(0.104

)0.03

0.21

2(0.102

)0.06

*−0.25

4(0.054

)−0.14

***

Con

stant

6.13

1(0.448

)7.93

5(0.372

)6.77

4(0.479

)4.72

4(0.472

)3.45

4(0.252

)

R2

0.11

***

0.10

***

0.08

***

0.18

***

0.06

***

Adj

R2

0.11

***

0.09

***

0.08

***

0.18

***

0.06

***

Step2

DEC-O

BJ

−0.07

3(0.075

)−0.03

0.06

1(0.064

)0.03

−0.00

2(0.081

)0.00

−0.10

1(0.081

)−0.03

−0.01

9(0.045

)−0.01

DEC-SUBJ

−0.24

7(0.179

)−0.05

0.30

1(0.140

)0.08

*0.61

1(0.165

)0.12

***

1.15

7(0.168

)0.22

***

0.25

8(0.094

)0.10

**

SE–ST

−0.30

5(0.088

)−0.09

***

0.10

5(0.083

)0.04

−0.03

4(0.103

)−0.01

0.14

3(0.108

)0.04

−0.21

6(0.060

)−0.12

***

PROC-O

BJ

0.37

4(0.132

)0.09

**0.27

9(0.093

)0.09

**−0.23

1(0.133

)−0.05

0.59

0(0.126

)0.14

***

−0.14

3(0.077

)−0.06

PROC-SUBJ

1.63

0(0.172

)0.36

***

1.12

9(0.132

)0.30

***

1.69

2(0.152

)0.36

***

1.22

2(0.154

)0.24

***

0.43

1(0.086

)0.17

***

PROD

VALUES

0.69

5(0.072

)0.27

***

nana

nana

0.37

3(0.080

)0.13

***

0.14

5(0.044

)0.10

***

BIO

VALUES

nana

0.16

2(0.064

)0.08

*na

na0.24

4(0.082

)0.09

**−0.02

8(0.046

)−0.02

RECVALUES

nana

nana

0.14

5(0.072

)0.06

*na

nana

na

Con

stant

2.00

0(0.497

)5.95

3(0.495

)4.74

4(0.606

)0.73

1(0.659

)2.89

7(0.378

)

R2

0.28

***

0.17

***

0.19

***

0.27

***

0.10

***

Adj

R2

0.27

***

0.17

***

0.19

***

0.27

***

0.09

***

ΔR²

0.16

***

0.08

***

0.11

***

0.09

***

0.03

***

Step3

DEC-O

BJ

−0.12

5(0.071

)−0.05

0.01

9(0.063

)0.01

−0.13

5(0.078

)−0.05

−0.19

4(0.076

)−0.07

*−0.04

6(0.044

)−0.03

DEC-SUBJ

−0.47

2(0.170

)−0.10

**0.13

4(0.142

)0.03

0.06

0(0.166

)0.01

0.63

0(0.164

)0.12

***

0.10

7(0.096

)0.04

SE–ST

−0.20

3(0.084

)−0.06

*0.14

0(0.082

)0.05

−0.02

9(0.097

)−0.01

0.16

7(0.101

)0.05

−0.19

2(0.059

)−0.10

***

PROC-O

BJ

0.19

4(0.126

)0.04

0.24

8(0.093

)0.08

**−0.18

6(0.126

)−0.04

0.47

0(0.119

)0.11

***

−0.10

0(0.076

)−0.04

PROC-SUBJ

1.15

4(0.169

)0.25

***

0.96

5(0.134

)0.26

***

1.34

9(0.147

)0.29

***

0.90

7(0.148

)0.18

***

0.33

0(0.085

)0.13

***

PROD

VALUES

0.37

1(0.074

)0.14

***

nana

nana

0.10

5(0.082

)0.04

0.01

4(0.048

)0.01

BIO

VALUES

nana

0.03

5(0.067

)0.02

nana

0.06

6(0.083

)0.02

−0.01

9(0.048

)−0.01

RECVALUES

nana

nana

0.01

6(0.071

)0.01

nana

nana

PROD_P

RIV

ATEFOI

1.10

8(0.137

)0.27

***

nana

nana

0.29

3(0.151

)0.07

0.40

8(0.088

)0.18

***

CON_P

UBLIC

FOI

nana

0.57

5(0.131

)0.15

***

1.02

8(0.160

)0.21

***

0.97

0(0.159

)0.19

***

0.02

4(0.093

)0.01

SOCIA

LFOI

0.38

4(0.098

)0.12

***

0.22

9(0.082

)0.09

**0.28

9(0.100

)0.09

**0.23

8(0.106

)0.07

*0.18

4(0.061

)0.11

**

Environmental Management (2020) 66:549–563 557

although not in relation to production and mitigation (sub-stitution) management. Results suggest that value priorities(i.e., production values) are particularly important for pro-duction management. Since situational constraints mayprevent values from having an impact on actual behavior(Steg et al. 2014; see also Põllumäe et al. 2014), the weakereffect of non-production values on management behaviorsin this sample may stem from the production-oriented focusof forestry in Sweden (Keskitalo et al. 2016; Andersson andKeskitalo 2018). Even though there are no regulatory bar-riers to alternative management, the production forestryculture may, through normative processes, facilitate pro-duction and discourage alternatives. The study furtherrevealed that the internalization of core interests (i.e., pro-duction versus consumption) in terms of forest owneridentities was relevant for management behaviors. Theresults are generally in line with depictions of identity as amediator between value priorities and behaviors (cf. Gate-rsleben et al. 2017). Previous studies have confirmed thatsocial factors play an important role for forest owners’behaviors (Ruseva et al. 2014; Eriksson 2018a). This studyadvances this line of research by outlining a potential psy-chological mechanism for how the social context mayinfluence behaviors. Owners interacting with other ownersin various ways are likely to internalize perceptions of beinga social owner, and this connectedness to others may in turnfacilitate an active management approach. Since the SocialFOI was positively associated with diverse managementstrategies, it is worth pointing out that the owners’ networksseem to facilitate different management objectives, despitethe emphasis on production in the Swedish forestry context.

Active or passive forest management approaches may beadvocated depending on, for example, the purpose of themanagement, such as maximizing certain forest functions ormultifunctionality (e.g., Hagerman and Pilai 2018; Cruz-Alonso et al. 2019; White and Long 2019; Williams andPowers 2019). Whereas this study showed that certainstructural characteristics were associated with managementinactivity (owning a smaller forest holding, being female,and owning forest in the north and middle regions inSweden) (cf. Eriksson 2018b), results further revealed thatan overall lesser focus on production (knowledge and valuepriorities) and a lower identification with other owners alsocharacterized management inactivity. Potentially reflectingthe production focus in this context but also that a norm ofactive management is remaining in Sweden despite thelower regulatory demands on management (Bush 2010).Nonresident owners, and owners living in an urban context,were not more likely to display inactivity, thus indicatingthat spatial distance to the forest do not necessarily mean alower involvement in management (cf. Huff et al. 2017).However, worth noticing is the importance of differentcompetences for an active forest management approachTa

ble3(con

tinued)

Produ

ction

Biodiversity

Recreation

Adaptation

Mitigatio

n(sub

stitu

tion)

B(SE)

βB(SE)

βB

(SE)

βB(SE)

βB(SE)

β

DISTANTFOI

−0.55

4(0.142

)−0.11

***

0.00

6(0.127

)0.00

−0.54

8(0.156

)−0.10

***

−0.72

8(0.153

)−0.14

***

−0.01

8(0.089

)−0.01

CENTRALFOI

−0.14

1(0.125

)−0.03

0.04

4(0.121

)0.01

0.35

2(0.147

)0.08

*0.30

5(0.145

)0.07

*−0.04

4(0.084

)−0.02

Con

stant

3.83

9(0.764

)4.90

3(0.702

)3.31

8(0.865

)1.13

3(0.874

)2.72

7(0.527

)

R2

0.36

***

0.20

***

0.28

***

0.36

***

0.14

***

Adj

R2

0.36

***

0.20

***

0.28

***

0.36

***

0.13

***

DEC-O

BJdeclarativeob

jectivekn

owledg

e,PROC-O

BJprocedural

objectivekn

owledg

e(PROD

prod

uctio

n,BIO

biod

iversity,RECrecreatio

n,MIT

mitigatio

n,andADAPTadaptatio

n).DEC-

SUBJdeclarativesubjectiv

ekn

owledg

e,PROC-SUBJprocedural

subjectiv

ekn

owledg

e(PROD

prod

uctio

n,BIO

biod

iversity,RECrecreatio

n,ADAPTadaptatio

n,andMIT

mitigatio

n).SE

–ST

self-enh

ancementversus

self-transcend

ence,PROD

VALUE

prod

uctio

nforest

values,BIO

VALUE

biod

iversity

forest

values,REC

VALUE

recreatio

nforest

values.PROD

PRIVATE

FOI

prod

uctio

n/privateforestow

neridentity,

CON

PUBLIC

FOIconsum

ption/pu

blic

forestow

neridentity,

SOCIALFOIsocial

forestow

neridentity,

DISTANTFOIdistantforestow

neridentity,

CENTRALFOIcentralforestow

neridentity.

nano

tapplicable

*p<0.05

;**p<0.01

;**

*p<0.00

1

558 Environmental Management (2020) 66:549–563

(i.e., more actual knowledge of biodiversity, recreation, andproduction management), showing that a broad range ofskills is needed for owners to actively manage their forest.

When interpreting the results of this study, somelimitations should be considered. Although a representativesample of forest owners in Sweden was surveyed andcalibrated weights were used to avoid biases, active forestowners are likely overrepresented in the sample since theyare likely more interested in the topic of the study. Themeasures were carefully developed and the internal relia-bility was generally good. However, despite being sig-nificant predictors, some of the scales measuring FOIdisplayed low reliability, indicating a need to develop thesemeasures, and validate them in future research. The studywas theoretically based, but since cross-sectional data

cannot support causality, experimental evidence is neededto confirm the effect of independent variables on manage-ment behaviors (e.g., by exploring how different knowledgeinterventions influence management behaviors). While anoverall assessment of the importance of psychologicalpredictors for management behaviors is frequently missingin previous studies, the level of explained variance of pro-duction and climate adaptation management behaviors wascomparable to results by Karppinen (2005) and Dreschelet al. (2017), and the level of explained variance in biodi-versity and recreation management was equivalent to that inthe study by Eriksson (2017). To develop the understandingof the individual drivers of forest management behaviors, itmay be valuable to consider interactions between knowl-edge and value priorities in future research (e.g., values may

Table 4 Hierarchical binary logistic regression analysis of management inactivity in three steps: (1) general variables (declarative knowledge andbasic values), (2) specific variables (procedural knowledge and forest values), (3) forest owner identities

Step 1 Step 2 Step 3

B (SE) Wald Exp (B) B (SE) Wald Exp (B) B (SE) Wald Exp (B)

DEC-OBJ −0.200 (0.059) 11.302*** 0.819 −0.111 (0.067) 2.702 0.895 −0.073 (0.073) 0.995 0.930

DEC-SUBJ −0.861 (0.109) 62.195*** 0.423 −0.195 (0.168) 1.356 0.822 −0.076 (0.179) 0.179 0.927

SE–ST 0.077 (0.072) 1.156 1.080 0.011 (0.086) 0.016 1.011 −0.043 (0.090) 0.232 0.958

PROC-OBJ PROD −0.433 (0.125) 11.898*** 0.649 −0.332 (0.134) 6.088* 0.718

PROC-OBJ BIO −0.371 (0.104) 12.652*** 0.690 −0.353 (0.109) 10.447*** 0.703

PROC-OBJ REC −0.320 (0.111) 8.268** 0.726 −0.344 (0.117) 8.678** 0.709

PROC-OBJ ADAPT 0.440 (0.116) 14.350*** 1.552 0.531 (0.124) 18.271*** 1.701

PROC-OBJ MIT 0.051 (0.121) 0.176 1.052 −0.022 (0.129) 0.030 0.978

PROC-SUBJ PROD −0.649 (0.175) 13.768*** 0.523 −0.426 (0.187) 5.207* 0.653

PROC-SUBJ BIO 0.197 (0.183) 1.158 1.218 0.277 (0.197) 1.987 1.320

PROC-SUBJ REC 0.077 (0.155) 0.247 1.080 0.089 (0.165) 0.294 1.094

PROC-SUBJ ADAPT −0.336 (0.164) 4.199* 0.715 −0.218 (0.173) 1.584 0.804

PROC-SUBJ MIT 0.082 (0.176) 0.216 1.085 0.075 (0.188) 0.160 1.078

PROD VALUES −0.415 (0.065) 40.482*** 0.660 −0.225 (0.072) 9.728** 0.798

BIO VALUES 0.009 (0.082) 0.011 1.009 0.029 (0.090) 0.103 1.029

REC VALUES 0.004 (0.075) 0.003 1.004 −0.031 (0.080) 0.149 0.970

PROD_PRIVATE FOI −0.492 (0.150) 10.751*** 0.612

CON_PUBLIC FOI 0.057 (0.146) 0.154 1.059

SOCIAL FOI −0.613 (0.113) 29.252*** 0.542

DISTANT FOI 0.352 (0.137) 6.609** 1.422

CENTRAL FOI −0.150 (0.129) 1.346 0.861

Constant 1.908 (0.339) 31.635*** 6.739 4.683 (0.619) 57.177*** 108.04 4.289 (0.852) 25.331*** 72.905

Nagelkerke R square 0.12 0.27 0.36

−2 Log likelihood 1134.25 1010.69 921.11

DEC-OBJ declarative objective knowledge, PROC-OBJ procedural objective knowledge (PROD production, BIO biodiversity, REC recreation,MIT mitigation, and ADAPT adaptation). DEC-SUBJ declarative subjective knowledge, PROC-SUBJ procedural subjective knowledge (PRODproduction, BIO biodiversity, REC recreation, ADAPT adaptation, andMIT mitigation). SE–ST self-enhancement versus self-transcendence, PRODVALUE production forest values, BIO VALUE biodiversity forest values, REC VALUE recreation forest values. PROD PRIVATE FOI production/private forest owner identity, CON PUBLIC FOI consumption/public forest owner identity, SOCIAL FOI social forest owner identity, DISTANTFOI distant forest owner identity, CENTRAL FOI central forest owner identity

*p < 0.05, **p < 0.01, ***p < 0.001

Environmental Management (2020) 66:549–563 559

be important for the acquisition of knowledge) (Thorn andBogner 2018). In addition, to determine the generality of theresults, there is a need to explore how different types ofknowledge (including local and traditional knowledge) andvalue priorities, as well as different indicators of manage-ment behaviors, are related in diverse samples and contexts.

Conclusion

This study distinguished between actual knowledge, con-fidence, and value priorities, and confirms the independenteffects of these factors along with forest owner identitieson management behaviors among forest owners. Its resultscontribute novel insights for the understanding of theindividual drivers of forest management behaviors, and theapproach may be drawn upon to advance the under-standing of the psychological basis of natural resourcemanagement more generally. In addition, the study hasimplications for governance. For example, more actualforest knowledge may not only lead to more informedmanagement decisions; this study suggests that increasingparticularly procedural knowledge of different manage-ment strategies may facilitate management. Althoughsupporting social networks and increasing actual knowl-edge of different management strategies are likely toencourage a more active management approach, boostingthe owner’s confidence to implement specific managementstrategies (e.g., production or recreation) is important inorder to facilitate particular management aims. Since amore varied forest may be more resistant to damage (e.g.,Jactel et al. 2017), there may be a need to ensure thatcultural and social factors do not prevent the diversity inowners’ value profiles from being realized in their man-agement practices. Moreover, by increasing the salience ofspecific owner identities in outreach to owners, specificforest functions may be encouraged.

Data Availability

The dataset analysed during the current study is availablefrom the corresponding author upon reasonable request afterthe completion of the project.

Acknowledgements The authors would like to thank the participatingforest owners for completing the survey and two anonymous reviewersfor their constructive comments. Open access funding provided byUmea University.

Funding This study was financed by Brattåsstiftelsen (grant number:F17:03).

Author Contributions Study design, questionnaire, analysis, and paperpreparation were performed by LE. CF has contributed to parts of the

questionnaire (mainly objective knowledge questions and forestmanagement behaviors).

Compliance with Ethical Standards

Conflict of Interest The authors declare that they have no conflict ofinterest.

Ethical Approval The study was conducted in accordance with theethical standards of the institutional and/or national research com-mittee and with the 1964 Helsinki declaration and its later amendmentsor comparable ethical standards.

Informed Consent Informed consent was obtained from all individualparticipants included in the study.

Publisher’s note Springer Nature remains neutral with regard tojurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, aslong as you give appropriate credit to the original author(s) and thesource, provide a link to the Creative Commons license, and indicate ifchanges were made. The images or other third party material in thisarticle are included in the article’s Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is notincluded in the article’s Creative Commons license and your intendeduse is not permitted by statutory regulation or exceeds the permitteduse, you will need to obtain permission directly from the copyrightholder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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